practical-ml

People talk about a language model's "memory" like it's some mysterious, ever-growing pool of understanding. It isn't. A context window is a fixed, countable, spendable resource — closer to a budget than to a brain — and understanding it that way changes how you should actually work with one.

"Machine learning" gets used as a synonym for "deep learning" so often that people assume every prediction problem needs a neural network, a GPU, and a few thousand dollars of cloud compute. Most of the time it doesn't. One of the most useful tools in the entire field is something you can explain on a napkin: the regression tree.